Jason
1.2 KiB
Philosophy
The philosophy behind this library is to provide a lightweight and flexible approach to leveraging language models (LLMs) to do structured output without imposing unnecessary dependencies or abstractions.
The instructor library serves as a bridge from text-based language model interaction to Object-Oriented Programming, seamlessly integrating LLMs into the programming paradigms we're familiar with. By treating LLMs as callable functions that return typed objects, instructor demystifies their complexity, making them more accessible for everyday projects. This approach maintains the flexibility and power of Python, letting you write custom code without unnecessary constraints.
- Define a Schema
#!python class StructuredData(BaseModel): - Encapsulate all your LLM logic into a function
#!python def extract(a) -> StructuredData: - Define typed computations against your data with
#!python def compute(data: StructuredData):
Please note that the library is designed to be adaptable and open-ended, allowing you to customize and extend its functionality based on your specific requirements.
If you have any further questions or ideas hit me up on twitter